the potential impact of changes in lower stratospheric...

The potential impact of changes in lower stratospheric water vapour on stratospheric temperatures over the past 30 years Article

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Maycock, A. C., Joshi, M. M., Shine, K. P., Davis, S. M. and Rosenlof, K. H. (2014) The potential impact of changes in lower stratospheric water vapour on stratospheric temperatures over the past 30 years. Quarterly Journal of the Royal Meteorological Society, 140 (684). pp. 21762185. ISSN 00359009 doi: https://doi.org/10.1002/qj.2287 Available at http://centaur.reading.ac.uk/37248/

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Quarterly Journal of the Royal Meteorological Society Q. J. R. Meteorol. Soc. 140: 2176–2185, October 2014 B DOI:10.1002/qj.2287

The potential impact of changes in lower stratospheric water vapouron stratospheric temperatures over the past 30 years

A. C. Maycock,a* M. M. Joshi,b K. P. Shine,c S. M. Davisd,e and K. H. Rosenlofd

aCentre for Atmospheric Science, Department of Chemistry, University of Cambridge, UKbSchool of Environmental Sciences, University of East Anglia, Norwich, UK

cDepartment of Meteorology, University of Reading, UKdNOAA/ESRL/Chemical Sciences Division, Boulder, CO, USA

eCIRES, University of Colorado, Boulder, CO, USA

*Correspondence to: A. C. Maycock, Centre for Atmospheric Science, Department of Chemistry, University of Cambridge,Cambridge, CB2 1EW, UK.E-mail: [email protected]

This study investigates the potential contribution of observed changes in lower stratosphericwater vapour to stratospheric temperature variations over the past three decades usinga comprehensive global climate model (GCM). Three case studies are considered. In thefirst, the net increase in stratospheric water vapour (SWV) from 1980–2010 (derived fromthe Boulder frost-point hygrometer record using the gross assumption that this is globallyrepresentative) is estimated to have cooled the lower stratosphere by up to ∼0.2 K decade−1

in the global and annual mean; this is ∼40% of the observed cooling trend over this period.In the Arctic winter stratosphere there is a dynamical response to the increase in SWV,with enhanced polar cooling of 0.6 K decade−1 at 50 hPa and warming of 0.5 K decade−1

at 1 hPa. In the second case study, the observed decrease in tropical lower stratosphericwater vapour after the year 2000 (imposed in the GCM as a simplified representation of theobserved changes derived from satellite data) is estimated to have caused a relative increasein tropical lower stratospheric temperatures by ∼0.3 K at 50 hPa. In the third case study, thewintertime dehydration in the Antarctic stratospheric polar vortex (again using a simplifiedrepresentation of the changes seen in a satellite dataset) is estimated to cause a relativewarming of the Southern Hemisphere polar stratosphere by up to 1 K at 100 hPa fromJuly–October. This is accompanied by a weakening of the westerly winds on the polewardflank of the stratospheric jet by up to 1.5 m s−1 in the GCM. The results show that, if the mea-surements are representative of global variations, SWV should be considered as importanta driver of transient and long-term variations in lower stratospheric temperature over thepast 30 years as increases in long-lived greenhouse gases and stratospheric ozone depletion.Key Words: temperature trends; stratosphere and climate; climate modelling; Antarctic dehydration; tropicalstratosphere; polar stratosphere

Received 19 December 2012; Revised 10 September 2013; Accepted 28 October 2013; Published online in Wiley OnlineLibrary 21 February 2014

1. Introduction

The concentration of water vapour in the stratosphere has beenshown to vary on interannual to multi-decadal time-scales. Forexample, it has been reported that there was a net increasein stratospheric water vapour (SWV) of ∼30% over the latetwentieth century (Rosenlof, 2001), followed by a sudden dropof ∼15% after 2000 (Randel et al., 2006). Such changes in SWVare thought to occur largely as a result of variations in tropical

[The copyright in this article was changed on 27 November 2014 after originalpublication.]

tropopause temperatures, which control the dehydration of air asit passes into the stratosphere (Mote et al., 1996; Fueglistaler andHaynes, 2005) and/or changes in the production of SWV frommethane oxidation (Le Texier et al., 1988). As a radiatively activespecies, changes in SWV may affect stratospheric temperatures(Maycock et al., 2011) and global-mean radiative forcing (Forsterand Shine, 2002), which can subsequently impact on the large-scale atmospheric circulation (Maycock et al., 2013).

Observations indicate that the lower stratosphere cooled by∼0.5 K decade−1 in the global mean between 1979 and 2007(Randel et al., 2009b). Although stratospheric cooling is expectedin response to increases in atmospheric carbon dioxide and

c© 2013 The Authors. Quarterly Journal of the Royal Meteorological Society published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,provided the original work is properly cited.

Lower Stratospheric Water Vapour and Temperature 2177

stratospheric ozone depletion, it is plausible that changes in SWVmay also have contributed to observed temperature trends. A keylimitation in quantifying this effect is the paucity of long-termglobal observations of SWV. Forster and Shine (1999) assumeda globally uniform increase of 0.7 ppmv as an approximationof the 1979–1997 SWV trend. They used an intermediatecomplexity global climate model (GCM) to show that the assumedchange in SWV had the greatest impact on temperatures in thelower stratosphere, with an annual-mean cooling at 50 hPa of∼0.4 K decade−1 in the Tropics and 0.8–1.3 K decade−1 in thepolar regions. Shine et al. (2003) estimated the global-meancooling due to the increase in SWV over a similar period tobe 0.1–0.2 K decade−1 in the upper stratosphere, but foundlarge uncertainties in the lower stratosphere across a numberof models. This was partly because the individual modellinggroups who carried out calculations had assumed different SWVtrends. However, it is also likely to be partly due to fundamentaldifferences in the representation of SWV in broad-band radiationcodes (Oinas et al., 2001; Maycock and Shine, 2012).

The goal of this study is to quantify the potential contributionof changes in lower stratospheric water vapour to seasonal andlonger-term stratospheric temperature variations over the pastthree decades. We limit our attention to the lower stratosphere,because this is where SWV has been observed best over thisperiod and also because it is the key region for SWV in termsof its impact on stratospheric temperatures and radiative forcing(Maycock et al., 2011; Solomon et al., 2010).

For the first time, observed latitude- and height-resolved SWVtrends are imposed in a comprehensive GCM. Three case studiesare investigated: the net increase between 1980 and 2010, the rapiddecrease in the tropical lower stratosphere after 2000 and thewintertime dehydration in the Antarctic lower stratosphere. Allof these cases have been documented in the literature (Nedoluhaet al., 2000; Rosenlof, 2001; Randel et al., 2006; Scherer et al.,2008; Hurst et al., 2011) and showcase the differing mechanismsthrough which SWV changes can impact on temperature trends,as well as including both tropical and extratropical variations.

To quantify the long-term trend, we use the latest analysis of theBoulder frost-point hygrometer dataset from balloon sondes (thelongest continuous record of SWV measurements) by Hurst et al.(2011), which resolves SWV variations in altitude and time at apoint location (40◦N, 105 ◦W). To characterize shorter time-scaleSWV variations, we use data from the Halogen Occultation Exper-iment (HALOE version 19) and Aura Microwave Limb Sounder(MLS version 2) satellite datasets. These datasets have been exten-sively validated in the literature (Harries et al., 1996; Lambert et al.,2007). HALOE data are adjusted to match the MLS values usinglatitude- and height-dependent offsets calculated from coincidentobservations taken during instrument overlap periods. However,these offsets do not impact on our experimental design, since weare primarily concerned with water vapour anomalies rather thanabsolute values on either interannual or seasonal time-scales. Forthe post-2000 case, the dataset used to design our model exper-iment primarily consists of HALOE data, with some MLS dataincluded in the period 2004–2005. We will show that the watervapour decrease in the combined HALOE/MLS dataset comparesvery well with a previous estimate based on HALOE data alone.The dataset used to characterize the seasonal dehydration in theAntarctic consists only of MLS data for the period 2005–2009.

The remainder of the article is laid out as follows: Section 2describes the comprehensive GCM and the set-up of the modelexperiments, section 3 describes the experiments carried outand presents our results and section 4 summarizes our findingsin the context of their implications for observed stratospherictemperature trends.

2. Method

This study presents sensitivity experiments designed to test theimpact of changes in SWV on stratospheric temperatures in a

comprehensive stratosphere-resolving atmospheric GCM. TheGCM is the same as that used by Maycock et al. (2013) andis described in detail by Hardiman et al. (2010) and Ospreyet al. (2010). Briefly, it is a 60 level version of the atmosphericcomponent of the Hadley Centre Global Environmental Model 1(HadGAM1) with an upper boundary at ∼84 km, which is run atN48 horizontal resolution (∼2.5◦ latitude×3.75◦ longitude). TheGCM simulates a reasonable representation of the climatologyand variability of the stratosphere (see the above articles andreferences therein for details).

HadGAM1 includes the Edwards and Slingo (1996) radiationcode updated to use the correlated-k method for calculatingtransmittances (Cusack et al., 1999). This code has been shownto systematically overestimate the stratospheric temperatureresponse and radiative forcing due to changes in SWV comparedwith more detailed radiation codes (Forster et al., 2011; Maycockand Shine, 2012). In this study, changes in SWV are onlyimposed in the lower stratosphere, where the radiation codeis associated with errors in the temperature change due to SWVperturbations of ∼30% for midlatitude summer and sub-Arcticwinter conditions and ∼15% for tropical conditions (Maycockand Shine, 2012). All of the results presented in section 3 havetherefore been scaled down by 30% to account for the knownerrors in the GCM’s radiation code. However, since the error fortropical conditions has been estimated to be smaller than this,our results will be a conservative estimate of what the ‘real world’response would be to an identical water vapour perturbation inthe Tropics.

Each case study consists of a reference experiment, without anychanges in SWV, and a perturbed experiment, with a fixed-in-timeSWV perturbation imposed for the duration of each simulation.The SWV perturbations are included in the GCM by artificiallymodifying the water vapour field passed into the radiation codeonly above the lapse-rate tropopause, which is diagnosed usingthe WMO (1957) lapse-rate definition at each radiation timestep.For reference, the three pairs of experiments presented in thisstudy and the SWV distributions prescribed in each of them arelisted in Table 1. Following Maycock et al. (2013), each referenceand perturbed experiment consists of a three-member ensemblerun for 23 years from January 1980–December 2002, giving atotal of 69 years of data. The simulations include time-varyingconcentrations of carbon dioxide, methane, nitrous oxide andchlorofluorocarbons. Volcanic aerosols are not included in anyof the simulations.

The model is forced with monthly mean sea-surfacetemperatures (SSTs) and sea-ice concentrations taken from theMet Office Hadley Centre’s SST and sea-ice dataset (HadISST:Rayner et al., 2003). The use of time-varying SSTs and sea icemeans that there is a more realistic signal-to-noise relationshipin the experiments, as well as enabling the effects of the SWVperturbations to be isolated from other sources of stratospherictemperature variability, such as the El Nino Southern Oscillation(ENSO). However, the use of non-interactive SSTs means thatthe radiative impact of the imposed changes in SWV on surfacetemperatures will not be fully captured in the experiments. Ozoneis prescribed as a zonal-mean monthly mean climatology frommerged satellite datasets averaged over the period 1979–2003(see Dall’Amico et al., 2010 for further details). The effectsof SWV perturbations on stratospheric chemistry are thereforenot included in the simulations; however, some of the possiblefeedbacks are discussed later in section 3.3.

Note that in all of the experiments the changes in SWV areimposed as fixed-in-time perturbations, rather than time-varyingtrends. The model set-up is therefore effectively a time-sliceconfiguration, with the exception of having time-varying SSTs,sea ice and long-lived greenhouse gas concentrations. It istherefore not reasonable to compare the temporal evolution ofthe simulated temperature changes with observations, but ratherthe focus here is on the implied net temperature changes due tothe SWV perturbations over specified time periods.

c© 2013 The Authors. Quarterly Journal of the Royal Meteorological Societypublished by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.

Q. J. R. Meteorol. Soc. 140: 2176–2185 (2014)

2178 A. C. Maycock et al.

Table 1. Description of the stratospheric water vapour fields for each of the three pairs of control and perturbed experiments discussed in this article. In all cases, thewater vapour below the lapse rate tropopause is left as the model’s own self-consistent free running tracer field.

Corresponding stratospheric water vapour distribution

Exp 1 ORIG Model’s own simulated stratospheric water vapour field.TREND As ORIG, but with 1980–2010 trend from Hurst et al. (2011) added as a constant-in-time height-dependent

perturbation at all latitudes (see Table 2).

Exp 2 ORIG As above.TROP As ORIG, but with post-2000 SWV decrease based on the combined HALOE/MLS dataset added as a

constant-in-time perturbation (see Figure 5(b)).

Exp 3 CTL Constant fixed 3 ppmv at all latitudes/altitudes above the tropopause.DEHYD As CTL, but with seasonal stratospheric Antarctic dehydration based on Aura MLS data included from

June–December.

3. Results

3.1. Multi-decadal variations in SWV: the 1980–2010 trend

Hurst et al. (2011) present an updated analysis of the frost-pointhygrometer record of SWV measurements taken at Boulder,Colorado. They provide estimates of the net change in SWVbetween March 1980 and January 2010 in 2 km layers forthe altitude range 16–28 km; for reference, these trends arereproduced in Table 2, along with their 95% confidence intervals.It is important to note that this ∼30 year period includes the netpositive trend between 1980 and 2000, the rapid decrease after2000 and the more gradual recovery to pre-2000 concentrationsin recent years (see Figure 4 of Hurst et al., 2011). Althoughthere are relatively large uncertainties in the trends, with thetypical 95% confidence intervals being ∼25% of the mean, forthe purposes of our experiments we assume that the best estimateis representative of ‘truth’. This seems reasonable, since we mustmake further, larger assumptions about the behaviour of SWV asdescribed below.

The SWV changes in Table 2 were added at all latitudes asa fixed-in-time perturbation to the model’s time-evolving SWVfield, using the method described in section 2. We therefore makethe large assumption that these single point measurements can beconsidered globally representative. We justify this approximationbecause the available in situ and satellite data suggest that a netpositive SWV trend was also observed across much of the globeduring this period (Rosenlof, 2001; Smith et al., 2001), albeit withlarge year-to-year variability. Since Hurst et al. (2011) do notprovide estimates of the SWV trend for altitudes less than 16 km,we make the further assumption that the value in the lowest layer(16–18 km) is representative of the trend at all altitudes downto the local tropopause. Given the known mechanisms for watervapour transport in the stratosphere, it is very unlikely that SWVtrends in the altitude range 16–28 km would occur in isolationfrom the layers above and below, and there is some observationalevidence that our assumption is reasonable (Fujiwara et al., 2010).However, no changes in SWV are imposed above 28 km in ourexperiment. This is mainly because, as described in section 1, it ischanges in lower stratospheric water vapour that have the greatestimpact on both stratospheric and tropospheric temperatures, butalso because the Boulder measurements do not extend into theupper stratosphere. SWV perturbations in the upper stratospherehave been shown to have a considerably smaller impact on localtemperature and global radiative forcing than equivalent changesin the lower stratosphere (Maycock et al., 2011; Solomon et al.,2010). Nevertheless, SWV trends at altitudes greater than 28 kmare likely to be comparable to, or greater than, those in therange 16–28 km because of the larger contribution of methaneoxidation in the upper stratosphere. The model set-up describedabove is referred to as the ‘TREND’ experiment. The baselineexperiment without any imposed changes in SWV is denoted as‘ORIG’.

Figure 1 shows the differences in zonal-mean seasonal-meantemperature (T) between the TREND and ORIG experimentsexpressed in terms of an effective trend (K decade−1) for (a)June–August (JJA) and (b) December–February (DJF) seasons.The grey shading indicates where the differences are found tobe statistically significant at the 95% confidence level usinga two-tailed Student’s t-test.∗ As expected, the increase inSWV causes cooling in the lower stratosphere. At a givenpressure level, the cooling at high latitudes is generally largerthan in the Tropics, which is consistent with the extratropicalenhancement of the cooling due to SWV found in other studies(Forster and Shine, 1999; Maycock et al., 2011). The peakmagnitude of the cooling tendency is ∼0.1–0.2 K decade−1 inthe Tropics and ∼0.2–0.3 K decade−1 in the extratropical andpolar regions. The main exception to this is in the NorthernHemisphere (NH) extratropics in DJF, where the cooling reaches∼0.5 K decade−1 over the Pole. There is also a statisticallysignificant warming of similar magnitude in the uppermoststratosphere and lower mesosphere (0.2–5 hPa). We performedfixed dynamical heating calculations (using the method of Felset al., 1980, not shown), which show that this warming cannotbe explained by radiative effects alone. This indicates that thereis a dynamical response to the imposed SWV perturbation in theNH winter polar stratosphere. This is confirmed by analysisof the Transformed Eulerian Mean mass circulation in thestratosphere (Andrews et al., 1987, not shown), which showsincreased downwelling motion (adiabatic warming) in the upperstratosphere and decreased downwelling (adiabatic cooling) inthe lower stratosphere. This is qualitatively consistent with theresponse to an increase in SWV in the lower stratosphere foundby Maycock et al. (2013, see their Figure 8). However, the precisemagnitude of the dynamical modification of the temperaturechange is subject to some uncertainty, given the relatively simplecorrection we have made to account for the known errors in theradiation code (see section 2).

Figure 2 shows the seasonal cycle of the effective temperaturetrend (K decade−1) due to the increase in SWV as a functionof latitude (φ) at 50 hPa. In the Tropics, the magnitude of thecooling trend is ∼0.1–0.25 K decade−1 throughout the year. Inthe Southern Hemisphere (SH) extratropics, the cooling trend is∼0.2–0.3 K decade−1 from December–July; however, there areno statistically significant changes at southern high latitudes fromAugust–November. In the NH extratropics, the cooling trend is∼0.1–0.2 K decade−1 from May–October. In boreal winter, thereis the suggestion of enhanced cooling at high northern latitudes.Although this is not statistically significant in the monthly meandata, it is a robust signal in the DJF mean (see Figure 1).

Figure 3 shows vertical profiles of the TREND-ORIG annual-mean T change (K decade−1) averaged over (a) the globe, (b)30◦S–30◦N, (c) 60–90◦N and (d) 60–90◦S. In all regions

∗The Student’s t-test is computed using the 3×23 = 69 years of data from eachexperiment, giving a combined sample size of 138.


Q. J. R. Meteorol. Soc. 140: 2176–2185 (2014)


Table 2. Values of the net change in stratospheric water vapour (ppmv) in 2 km layers between March 1980 and January 2010 from the Boulder frost-point hygrometerdataset and reproduced from Hurst et al. (2011). The values in brackets denote the 95% confidence limits.

Altitude interval16–18 km 18–20 km 20–22 km 22–24 km 24–26 km

1980–2010 SWV trend (ppmv) 0.71 (0.26) 0.80 (0.24) 1.12 (0.25) 1.25 (0.23) 1.20 (0.19)

−90 −60 −30 0 30 60 90

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Figure 1. The T trend (K decade−1) due to the change in SWV between 1980 and 2010 shown in Table 2 calculated from the difference between the TREND andORIG experiments for (a) JJA and (b) DJF. The contour interval is 0.1 K decade−1. The thick solid contour denotes the zero line. The shading indicates the regionswhere the differences are statistically significant at the 95% confidence level. Note that the differences shown in all plots have been scaled down by 30% to account forthe known errors for SWV in the GCM radiation code.

T trend (K decade−1) 1980–2010 - 50 hPa

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Figure 2. Latitude–time plot of the simulated temperature trend (K decade−1) at50 hPa due to the imposed 1980–2010 SWV trend. The shading indicates wherethe differences are statistically significant at the 95% confidence level. The contourinterval is 0.1 K decade−1. An additional contour is plotted at −0.24 K decade−1

to highlight the changes in the Tropics. The thick solid contour denotes the zeroline.

considered, the cooling trend due to the change in SWV hasa peak magnitude of 0.20–0.25 K decade−1. In the global mean,there is a cooling trend between 10 and 200 hPa, which is largest inthe layer 30–50 hPa. In the extratropics, the peak cooling extendsfrom 30–150 hPa because of the lower height of the tropopause.

We now compare our model results with estimates of theobserved temperature trend over this period. The black line inFigure 4 shows the temperature differences from Figure 3(a)weighted by the Microwave Sounding Unit (MSU) TemperatureLower Stratosphere (TLS) weighting function. This weightingfunction peaks at ∼17 km and samples in the altitude range10–30 km, so it is appropriate for investigating the impact oflower stratospheric water vapour changes. The dashed lines show±2σ of the interannual variability from the model to give anestimate of the uncertainty in the inferred temperature trend. Thegrey line is the observed MSU TLS trend for the period 1979–2009reproduced from Figure 8 of Seidel et al. (2011). For the MSUdata, the dashed lines show the ±2σ estimates due to the internal

data uncertainties (Mears et al., 2011). Note, however, that thisdoes not reflect the uncertainty in the estimated linear trend itself.The total uncertainty is therefore larger than that shown here,particularly at high latitudes in winter when there is considerableyear-to-year variability (see Figure 9 of Seidel et al., 2011) and wetherefore exclude these regions from our comparison.

The observed MSU TLS cooling trend is ∼0.3 K decade−1 inthe Tropics and subtropics. Figure 4 shows that the trend inSWV could have contributed up to 30–40% of this cooling.Our experiment also suggests that the SWV trend could havehad a larger impact on high-latitude wintertime temperatures,but as noted above the observed trends in these regions arecurrently less well constrained. Randel et al. (2009b) estimateda global mean annual mean lower stratospheric cooling trendof ∼0.5 K decade−1 between 1979 and 2007 using data from anumber of satellite instruments and radiosonde databases. Figure3(a) indicates that the SWV trend could have contributed up to40–50% of the global mean cooling trend.

These results reinforce the conclusion of earlier studies thatwater vapour makes an important contribution to the radiativebudget of the lower stratosphere and changes in its concentrationcan play a key role in determining temperature trends in thisregion (Shine et al., 2003).

3.2. Decadal variations in SWV: the rapid decrease after 2000

The rapid decrease in tropical SWV after 2000 was observed inseveral satellite and in situ measurement datasets (Solomon et al.,2010), and has been linked to changes in the strength of theBrewer–Dobson circulation (Randel et al., 2006) and variationsin tropical west Pacific SSTs (Rosenlof and Reid, 2008). The dropin SWV persisted for several years, although concentrations havenow virtually returned to pre-2000 levels (Hurst et al., 2011).

Figure 5(a) shows the difference in the annual-mean specifichumidity (ppmv) between the four-year periods June 2001–May2005 and January 1996–December 1999 calculated from thecombined HALOE/MLS dataset. This is very similar to theequivalent calculation by Solomon et al. (2010) using HALOEdata (see their Figure 1(b)). There was a decrease in water vapourover much of the stratosphere after 2000, with a peak reductionof ∼0.5 ppmv in the tropical lower stratosphere between 15◦S


Q. J. R. Meteorol. Soc. 140: 2176–2185 (2014)


Annual-mean T (K) diff - global

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Figure 3. Vertical profiles of the annual-mean T trend (K decade−1) for the TREND experiment averaged over (a) the globe, (b) the Tropics (30◦N–30◦S), (c) theNorthern Hemisphere extratropics (60–90◦N) and (d) the Southern Hemisphere extratropics (60–90◦S). The thick lines denote where the differences are statisticallysignificant at the 95% confidence level.

T trend - MSU TLS weighting function

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TREND exp.Observations

Figure 4. The latitudinal distribution of the annual-mean T trend (K decade−1)for the TREND experiment weighted by the MSU TLS weighting function (black)and the observations for the period 1979–2009 reproduced from Seidel et al.(2011) (grey). The dotted lines denote the ±2σ limits and the dashed line denotesthe zero trend line.

and 15◦N. It has been suggested that the radiative forcing due tothe decrease in SWV may have contributed to decadal variabilityin global mean surface temperature (Solomon et al., 2010). Inaddition, such a change would also be expected to impact on

tropical lower stratosphere temperatures, and it is this effect thatwe consider here.

Figure 5(b) shows an analytic function designed to be anapproximate representation of the observed change in SWVshown in Figure 5(a). The three-member ensemble experimentwas repeated with the SWV anomaly in Figure 5(b) added asa fixed-in-time perturbation to the model’s time-evolving watervapour field. This experiment is referred to as ‘TROP’.

Figure 6 shows the seasonal-mean absolute differences in T (K)between the TROP and ORIG experiments for (a) JJA and (b)DJF. The decrease in SWV causes a relative increase in tropicallower stratospheric temperatures by up to 0.3 K at ∼60–70 hPa.The amplitude of the change in T decreases with increasinglatitude and height, but the signal extends out to around |φ|=60◦in both hemispheres. Since the effect of the change in SWVon lower stratospheric temperature is small and positive, whichwould imply a weak negative feedback on water vapour transportinto the stratosphere, the persistence of the post-2000 episode islikely to be related to changes in the tropical tropopause layer thatare unrelated to the SWV evolution (i.e. SWV is responding toa temperature change forced by dynamical changes, e.g. Randelet al., 2006; Rosenlof and Reid, 2008). Note that other changesthat have been associated with the post-2000 episode, includingincreased tropical upwelling and decreased ozone concentrations(Randel et al., 2006), would induce a cooling of the tropical lowerstratosphere. There is no evidence of there being a detectablechange in zonal winds in the GCM due to the imposed SWVperturbation (not shown).

Figure 7 shows the vertical profile of the annual-mean Tdifference (K) between the TROP and ORIG experiments averagedover 30◦S–30◦N. The change in SWV has the largest impact ontropical temperatures at ∼50 hPa, which coincides with the peakof the SWV perturbation as shown in Figure 5(b). The magnitudeof the temperature change decreases rapidly with altitude above


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HALOE/MLS SWV mixing ratio (ppmv) post-2000

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Figure 5. (a) The difference in SWV volume mixing ratio (ppmv) between the four-year periods June 2001–May 2005 and January 1996–December 1999 in thecombined HALOE/MLS dataset. (b) The quasi-realistic SWV perturbation (ppmv) imposed in the TROP experiment. The contour interval is 0.1 ppmv. To highlightthe region of interest, data are only shown for −60◦ ≤ φ ≤60◦ and 200–5 hPa.

−60 −30 0 30 60

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Figure 6. The differences between the TROP and ORIG experiments in T (K) for (a) JJA and (b) DJF seasons. The contour interval is 0.1 K. The thick solid contourdenotes the zero line. The shading indicates where the differences are statistically significant at the 95% confidence level. The domain shown is the same as in Figure 5.

Annual-mean T (K) diff - tropics (30°S–30°N)

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Figure 7. Vertical profile of the annual-mean difference in T (K) between theTROP and ORIG experiments averaged over the Tropics (30◦N–30◦S). The thickline denotes where the differences are statistically significant at the 95% confidencelevel.

and below this level, and there are no statistically significantchanges outside the layer 20–100 hPa.

Although there was no apparent step-wise change in observedtropical lower stratospheric temperatures after the year 2000(Randel et al., 2009b), a signal of this magnitude and persistencemay be hard to detect given the relatively large interannualvariability in this region. Temperatures in this region are sensitiveto many factors including ENSO (Randel et al., 2009a), changesin the strength of tropical upwelling (Yulaeva et al., 1994) and

local ozone concentrations (Solomon et al., 2012), which makes itdifficult to separate the effect of SWV from other climatic drivers.However, our experiment shows that, all things being equal,the observed decrease in SWV would have raised tropical lowerstratospheric temperatures by ∼0.3 K in the period 2001–2005.

3.3. Seasonal variations in SWV: dehydration in the Antarcticpolar vortex

The formation of polar stratospheric ice clouds (type-II PSCs) canresult in irreversible dehydration of the lower to mid stratosphere,since the ice particles sediment out and evaporate when theyreach warmer air at lower altitudes (Vomel et al., 1994). PSCsare more common in the Antarctic than in the Arctic, since thetemperature at 80◦S typically decreases to ∼185 K at 50 hPa inwinter, compared with ∼202 K at 80◦N (SPARC, 2002). Bothin situ and satellite instruments have observed dehydration inthe Antarctic stratospheric polar vortex (Vomel et al., 1994;Nedoluha et al., 2000). The formation of stratospheric clouds willimpact directly on the local heating rate. The effect of a 100%coverage in type-II PSCs has been estimated to be an increase inthe cooling rate of up to ∼0.2 K day−1 poleward of 75◦S and adecrease of ∼0.2 K day−1 equatorward of 75◦S (Hicke and Tuck,2001). Here, we will not consider the direct effect of PSCs onstratospheric heating rates, but rather we focus on the impactof the dehydration itself on stratospheric temperatures, which toour knowledge has not been quantified previously. Although thisseasonal dehydration is a climatological feature in the Antarctic(Ramaswamy, 1988; Vomel et al., 1994), its magnitude andpersistence could change as a result of stratospheric temperature


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trends and/or SWV trends. It is therefore important to investigatethe impact of dehydration on the stratosphere, since it has thepotential to contribute to model biases and/or trends in polartemperatures.

Figure 8(a) shows the specific humidity at 100 hPa from MLSdata averaged over the period 2005–2009. The seasonal cycle inthe SH polar-cap average (φ >60◦S) SWV mixing ratio shows apeak change of −1.3 ppmv between April and September. Thisdehydration typically occurs in the altitude range ∼12–24 km(Nedoluha et al., 2000). The values compare well with estimatesof the dehydration derived from other data sources (see e.g.Figure 6.31 of SPARCCCMVal (2010) and Figure 3 of Nedoluhaet al. (2000)). Figure 8(b) shows an analytic function designed toapproximately capture the seasonal cycle in specific humidity inFigure 8(a). The wintertime anomalies have been defined relativeto an idealized uniform summertime background concentrationof 3 ppmv, and there is therefore a constant offset of ∼1 ppmvbetween the water vapour mixing ratios shown in Figure 8(a)and (b). However, the seasonal cycle of polar cap SWV for theanalytic function shows a peak change of −1.1 ppmv, whichcompares well with the MLS data.

The three-member ensemble GCM experiment was repeatedwith the SWV distribution in Figure 8(b) imposed uniformly inthe pressure range 30–190 hPa. Everywhere else and at all othertimes the SWV concentration takes a fixed value of 3 ppmv. Thismodel set-up is referred to as the ‘DEHYD’ experiment. Thereference experiment in this case, which is referred to as ‘CTL’, istherefore a simulation in which the water vapour concentrationtakes a constant fixed-in-time value of 3 ppmv everywhere in thestratosphere (see Maycock et al., 2013, for more details).

Figure 9 shows the monthly mean differences in T (K)between the DEHYD and CTL experiments in the SH forJuly–December ((a)–(f)). Outside these months there are nostatistically significant changes in temperature. The impactof the dehydration is first evident in July, when there is arelative warming of ∼0.5 K at φ >75◦S. This signal increasesin magnitude over the winter and reaches a maximum of∼1.1 K at φ >80◦S in September. The change in the polar-cap average T at 150 hPa is 0.4, 0.6 and 0.2 K in August,September and October, respectively. This is at least an orderof magnitude smaller than the impact of ozone depletion ontemperatures in the Antarctic stratosphere, which is estimatedto have caused a relative cooling of ∼7 K at similar altitudescompared with pre-1970 conditions (Thompson and Solomon,2002).

The relative warming over the polar cap shown in Figure 9causes a slight weakening of the background westerlies on thepoleward flank of the stratospheric jet (not shown). The decreasein zonal-mean zonal wind (u) has a maximum amplitude of∼1.5 m s−1 between 60 and 75◦S and 5–50 hPa in September.The mean background wind in this region in the GCM rangesfrom ∼30–50 m s−1, so this represents a deceleration of ∼2–5%.There are no significant changes in u from October–December.However, unlike the case of ozone depletion, which has resultedin a poleward shift in the tropospheric midlatitude jet in australspring/summer in recent decades (Polvani et al., 2011), there is noevidence of there being a change in the tropospheric circulationin response to the imposed Antarctic dehydration.

The impact of ozone depletion on stratospheric temperaturespeaks in October–November (Thompson and Solomon, 2002).The largest changes in T in response to the dehydration are foundin August–September in the GCM. The signal of dehydrationin the Antarctic stratosphere therefore peaks several monthsearlier than that of ozone depletion. In addition to the effectson temperature, the dehydration could also impact on ozonedepletion in austral spring, for example by altering chemicalreaction rates and the availability of water vapour for chemicalinteractions. There is also the potential for a negative feedback notincluded in these simulations, since the effect of the dehydration

is to increase stratospheric temperatures, which to first orderwould make type-II PSCs less likely to form.

4. Conclusions

This study has investigated the potential direct impact of observedchanges in stratospheric water vapour (SWV) on stratospherictemperatures in a comprehensive global climate model (GCM).Three case studies for SWV have been investigated: the long-termnet increase from 1980–2010, the rapid decrease in the tropicallower stratosphere after 2000 and the seasonal dehydration thatoccurs in the Antarctic stratospheric polar vortex.

The GCM’s radiation code contains known biases in itsrepresentation of stratospheric water vapour (Maycock andShine, 2012). We therefore scaled down the temperature changessimulated in the model by 30% to enable a fairer comparison withobservations. This is the estimated magnitude of the differencein the fixed dynamical heating temperature change for SWVcompared with a more detailed radiation code for midlatitudeand extratropical conditions. However, the relative error wasfound to be smaller for tropical conditions (∼15%), which meansthat our results are likely to be a conservative estimate of whatthe ‘real world’ response would be to an identical water vapourperturbation in the Tropics.

The paucity of long-term continuous global measurementsmakes it challenging to quantify long-term changes in SWVand this issue has been discussed at length in the literature.Here we have used the estimated SWV trends in the altituderange 16–26 km over the period 1980–2010 provided by Hurstet al. (2011), which are derived from frost-point hygrometermeasurements taken at Boulder, Colorado (40◦N, 105 ◦W). Toquantify the contribution of long-term changes in SWV tostratospheric temperature trends using a GCM, we have madefour key assumptions.

• The best estimates provided by Hurst et al. (2011) arerepresentative of ‘truth’, i.e. we do not account foruncertainties in the trends, which amount to a 95%confidence interval of ∼25% of the mean value.

• The point measurements taken at Boulder are representa-tive of global changes.

• The SWV change in the 16–18 km layer is representativeof trends at all altitudes down to the local tropopause.

• The effect of SWV in isolation can be consideredrepresentative of its effect when a combination of forcingsis present (e.g. changes in carbon dioxide, ozone and SWV).

With these caveats, the net increase in SWV from 1980–2010is associated with a cooling of the lower stratosphere of up to0.24 K decade−1 at 50 hPa in the annual and global mean. This isat the lower end of the estimated cooling trend due to SWV forthe period 1980–2000 presented by Shine et al. (2003). Forsterand Shine (1999) calculated a cooling trend of ∼0.4 K decade−1 at50 hPa in the Tropics due to a globally uniform increase in SWVof 0.7 ppmv. This perturbation is comparable to that imposed inthe TREND experiment (although theirs is not height-varying)and therefore the magnitude of the temperature trend calculatedhere is around a third smaller than that of Forster and Shine(1999), but within the range found in other studies (Shine et al.,2003; Seidel et al., 2011).

In the Arctic polar stratosphere, there is a dynamical response tothe increase in SWV in wintertime, with increased downwelling(adiabatic warming) in the upper stratosphere and decreaseddownwelling (adiabatic cooling) in the lower stratosphere. Thisenhances the radiatively driven cooling in the lower stratosphereby around a factor of three and causes a relative warming of∼0.5 K decade−1 in the upper stratosphere and lower mesosphere.This is qualitatively consistent with the dynamical response to anincrease in lower stratospheric water vapour found by Maycocket al. (2013).


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SWV mixing ratio (ppmv) 100 hPa - Aura MLS

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Figure 8. Latitude–time plots of the monthly mean SWV volume mixing ratio (ppmv) at 100 hPa for (a) Aura MLS data averaged over 2005–2009 and (b) thequasi-realistic SWV anomaly imposed in the DEHYD experiment. The contour interval in both panels is 0.4 ppmv.

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Figure 9. Plots of the monthly mean differences in T (K) between the DEHYD and CTL experiments for (a)–(f) July–December, respectively. The contour intervalis 0.2 K. The thick solid contour denotes the zero line. The shading indicates where the differences are statistically significant at the 95% confidence level. To highlightthe region of interest, data are only shown south of 45◦S and in the pressure range 300–10 hPa.

Several in situ and satellite datasets suggest that there was arapid decrease in tropical lower stratospheric water vapour of∼15% after 2000 (Solomon et al., 2010). Although there hasbeen considerable interest in the radiative forcing associated withthis change, its impact on stratospheric temperatures has notbeen previously quantified. We have shown that the decreasein SWV would have caused a relative warming of the tropicallower stratosphere by ∼0.3 K, which is roughly one third of theestimated cooling due to ozone depletion in this region overrecent decades (Polvani and Solomon, 2012). It is important tonote that there is the potential for a negative feedback to takeplace for tropical SWV perturbations, since a decrease in watervapour warms the tropopause region, which to first order wouldbe expected to decrease the dehydration of air entering into thestratosphere.

The formation of ice clouds in the Antarctic polar vortexleads to irreversible dehydration of air in the altitude range∼12–24 km. Past studies have considered the direct impactof polar stratospheric clouds (PSCs) on stratospheric heatingrates, but to our knowledge the impact of the dehydration ontemperatures has not been previously quantified. The relativechange in polar-cap specific humidity at 100 hPa is −1.3 ppmv

between April and September in Aura Microwave Limb Sounder(MLS) data. When imposed in the GCM, the observed wintertimedehydration causes a relative warming of the polar lowerstratosphere from July–October by up to ∼1 K. This causes aslight weakening of the westerlies on the poleward flank of thestratospheric jet by up to 1.5 m s−1 in September. The impact ofthe dehydration on the stratosphere peaks 1–2 months earlier,but is considerably weaker than the effects of stratospheric ozonedepletion.

In our simulations, none of the changes in SWV investigatedhad a detectable impact on the tropospheric circulation. Thisindicates that it is larger SWV trends, such as those simulatedby some chemistry–climate models in response to increasesin anthropogenic greenhouse gas emissions (Gettelman et al.,2010), that are more likely to be important for stratospheric andtropospheric circulation patterns (Joshi et al., 2006; Maycocket al., 2013). However, the results presented here reinforceearlier studies, which demonstrate that observed changes in SWVcould have made a significant contribution to the evolutionof stratospheric temperatures (Shine et al., 2003). With thecaveat that the Boulder data have been assumed to be globallyrepresentative, our results show that SWV changes may have been


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as important as carbon dioxide and ozone for driving global lowerstratospheric temperature trends over the past three decades. It istherefore a priority that SWV should continue to be monitoredin the future, so that its role in climate can be better understoodand quantified.

Acknowledgements

ACM was supported by a NERC PhD studentship at the Universityof Reading and a CASE award from the UK Met Office. MMJwas funded by NCAS-Climate, which is a NERC funded researchcentre. The authors thank the three anonymous reviewers fortheir suggestions on how to improve the manuscript.

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